SKILL.md
agentforce-architecture-analyze — declared architecture snapshot
Design-time metadata tree for one Agentforce agent: planner → topics → actions → flows → Apex → prompts → NGA plugins. Reads declared metadata only — BotDefinition, GenAiPlanner*, GenAiPlugin*, GenAiFunction*, Flow, ApexClass, GenAiPromptTemplate. Does not read runtime audit rows.
Runtime budget: 30–45s typical, ≤60s hard cap on reference fixtures. Sequential baseline would be 90–220s; parallel Tooling SOQL fan-out delivers a 3–5× speedup. Large bots with many flows scale approximately linearly — each flow metadata retrieve is one round-trip.
Runs inline — no subagent. Every phase is deterministic file processing.
If the user hasn't named an agent
Trigger condition: $ARGUMENTS names no agent (no --agent flag and no exact BotDefinition API name in the prose). Never invent an agent name. Instead, discover what the org actually contains — one read-only query, no pipeline yet. Use the --org alias if given, otherwise the default target org (omit --target-org):
sf data query --query "SELECT DeveloperName, MasterLabel FROM BotDefinition ORDER BY DeveloperName" \
[--target-org <alias>] --json
If the user gave no org alias, the pipeline block defaults --org to the CLI default target org itself (sf config get target-org --json → .result[0].value) — you don't need to resolve it.